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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Topic Drift Detector Model
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+
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+ ## Version: v20241225_085248
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+
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+ This model detects topic drift in conversations using an enhanced attention-based architecture.
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+
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+ ## Model Architecture
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+ - Multi-head attention mechanism
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+ - Bidirectional LSTM for pattern detection
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+ - Dynamic weight generation
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+ - Semantic bridge detection
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+
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+ ## Performance Metrics
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+ ```txt
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+ === Full Training Results ===
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+ Best Validation RMSE: 0.0107
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+ Best Validation R²: 0.8867
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+
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+ === Test Set Results ===
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+ Loss: 0.0002
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+ RMSE: 0.0129
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+ R²: 0.8373
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+
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+ ```
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+
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+ ## Training Curves
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+ ![Training Curves](plots/v20241225_085248/training_curves.png)
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+
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+ ## Usage
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+ ```python
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+ import torch
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+
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+ # Load model
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+ model = torch.load('models/v20241225_085248/topic_drift_model.pt')
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+
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+ # Use model for inference
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+ # Input shape: [batch_size, sequence_length * embedding_dim]
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+ # Output shape: [batch_size, 1] (drift score between 0 and 1)
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+ ```